Where do I find my AppLovin API keys?

You can find your Report Key and Management Key in the AppLovin dashboard under **Account > Keys**.

What is the difference between the Report Key and Management Key?

The Report Key is used for read-only access to performance data, while the Management Key is required for making changes to campaigns and ad units.

How often is user-level data updated?

User-level ad revenue data is typically available approximately 8 hours after the end of the UTC day.

AppLovin MCP Server for CrewAI 7 tools — connect in under 2 minutes

Name: AppLovin
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 7 Tools Framework

Connect your CrewAI agents to AppLovin through Vinkius, pass the Edge URL in the `mcps` parameter and every AppLovin tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="AppLovin Specialist",
    goal="Help users interact with AppLovin effectively",
    backstory=(
        "You are an expert at leveraging AppLovin tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in AppLovin "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 7 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About AppLovin MCP Server

The AppLovin MCP Server provides your AI agent with a powerful interface to your AppLovin and MAX mediation platforms. Gain instant insights into your monetization and user acquisition performance using simple natural language.

When paired with CrewAI, AppLovin becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call AppLovin tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

Key Features

MAX Reporting — Access aggregated performance data for your MAX mediation, including revenue, impressions, and eCPM.
User-Level Insights — Retrieve detailed revenue reports aggregated per user or per impression for granular analysis.
Cohort Analytics — Monitor user retention and long-term value using MAX cohort reports.
AppDiscovery Management — Track the performance of your UA campaigns and monitor growth trends.
Campaign & App Inventory — List all active campaigns and tracked apps in your AppLovin account.
Multi-Key Authentication — Securely uses both Report and Management keys to provide a comprehensive set of tools.

Benefits for Teams

Ad Ops Managers — Quickly audit monetization performance and eCPM trends without manual dashboard exports.
UA Specialists — Monitor campaign spend and performance across AppDiscovery using natural language.
Growth Engineers — Analyze user-level revenue and cohort data to optimize long-term retention and ROI.

The AppLovin MCP Server exposes 7 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect AppLovin to CrewAI via MCP

Follow these steps to integrate the AppLovin MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 7 tools from AppLovin

Why Use CrewAI with the AppLovin MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with AppLovin through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

AppLovin + CrewAI Use Cases

Practical scenarios where CrewAI combined with the AppLovin MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries AppLovin for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries AppLovin, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain AppLovin tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries AppLovin against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

AppLovin MCP Tools for CrewAI (7)

These 7 tools become available when you connect AppLovin to CrewAI via MCP:

get_account_check

Verify AppLovin account connection

get_app_discovery_report

Get performance data for UA campaigns (AppDiscovery)

get_max_cohort_report

Get cohort analysis reports for MAX

get_max_report

Use columns, start, and end parameters. Get aggregated performance data for MAX mediation

get_user_ad_revenue_report

Get revenue data aggregated per user or per impression

list_apps

List apps tracked in your AppLovin account

list_campaigns

List UA campaigns from the management API

Example Prompts for AppLovin in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with AppLovin immediately.

"Show me the MAX revenue report for yesterday."

"List all active UA campaigns in AppLovin."

"Give me a cohort report for user retention from last month."

Troubleshooting AppLovin MCP Server with CrewAI

Common issues when connecting AppLovin to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

AppLovin + CrewAI FAQ

Common questions about integrating AppLovin MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.